DISCRIMINATIVE CONTROL OF THERAPISTS' PERFORMANCE1

In order to examine therapists' discriminative responding to normal and idiosyncratic patient responses, naive subjects were presented with a simulated “patient” for treatment. The subjects were made to believe they were reinforcing normal verbalizations emitted by this patient In fact, they were listening to a tape on which normal and idiosyncratic verbalizations had been recorded. Different probabilities of normal and idiosyncratic “patient” verbalizations could be presented to the subjects by means of a digital programming unit. In one of a number of conditions, the subjects' accurate reinforcing responses were followed by an increased probability of the patient's normal verbalizations. Accurate reinforcing responses emitted by the subjects were brought under the control of normal and idiosyncratic patient responses, by use of contingent feedback, change in patient responding, and monetary reinforcers. When the patient's normal verbalizations increased in probability, so did the subjects' accurate reinforcing responses following the patient's normal verbalizations, and to a lesser degree, the subjects' inaccurate reinforcing responses following the patient's idiosyncratic verbalizations. When the patient's idiosyncratic verbalizations increased in probability, the subjects' accurate and inaccurate reinforcing responses decreased in probability. The clinical implications of these tendencies are discussed.     

An elementary student as a behavioral engineer

Four first-grade public school students exhibited non-study behaviors during a period when all children were to study individually. A fifth-grade student modified the maladaptive behaviors of the four first-grade students. Lights on the four students' desks, which were associated with opportunity for reinforcement, rapidly brought study behavior under stimulus control. Differential reinforcement of other behaviors dramatically decreased studying. Reinforcement was reinstituted and studying returned to a high and stable rate. Surreptitious post-experimental observation using closed-circuit TV indicated that the behavioral changes effected during the experimental phases were partially maintained by the regular classroom environment. A replication of the baseline phase with the observer in the classroom produced an increase in the rate of study behavior, indicating that the observer's presence acted as a discriminative stimulus for studying. An additional contingency requiring improved academic behavior was imposed before the fifth grader was given the opportunity to engage in the behavior modification experiment.     

Counselling of alcohol-dependents based on a model of change to abstinence

A model of change to abstinence in alcohol-dependents is presented based on the theory of reasoned action of Ajzen & Fishbein. The model includes attitudes, defence mechanisms and norms about aspects of alcohol consumption. An empirical study supports elements of the model. Conclusions pertinent to the counselling process are drawn.     

The short-term storage as a buffer memory between long-term storage and the motor system: A simultaneous-processing model

It is assumed that in a free-recall task the short-term store serves as a memory buffer between the long-term store and a final motor stage of word production. Because of this the retrieval process in long-term store is not hindered by the final motor stage of word production since continued output from the long-term store queues in the buffer for motoric processing. Otherwise a time consuming communication between the two processes would be necessary. A stochastic model of this conceptualization is provided to predict the temporal course of free recall as well as a paradigm in which the contribution of the short-term store in free recall can be studied. The experimental results from this paradigm were used to test the model and to estimate short-term storage capacity on the basis of the time course of free recall. The model predictions were in good agreement with the data and the capacity estimate coincides well with estimates found by totally different methods reported in the literature.     

A 2 × 2 taxonomy of multilevel latent contextual models: accuracy-bias trade-offs in full and partial error correction models

In multilevel modeling, group-level variables (L2) for assessing contextual effects are frequently generated by aggregating variables from a lower level (L1). A major problem of contextual analyses in the social sciences is that there is no error-free measurement of constructs. In the present article, 2 types of error occurring in multilevel data when estimating contextual effects are distinguished: unreliability that is due to measurement error and unreliability that is due to sampling error. The fact that studies may or may not correct for these 2 types of error can be translated into a 2 × 2 taxonomy of multilevel latent contextual models comprising 4 approaches: an uncorrected approach, partial correction approaches correcting for either measurement or sampling error (but not both), and a full correction approach that adjusts for both sources of error. It is shown mathematically and with simulated data that the uncorrected and partial correction approaches can result in substantially biased estimates of contextual effects, depending on the number of L1 individuals per group, the number of groups, the intraclass correlation, the number of indicators, and the size of the factor loadings. However, the simulation study also shows that partial correction approaches can outperform full correction approaches when the data provide only limited information in terms of the L2 construct (i.e., small number of groups, low intraclass correlation). A real-data application from educational psychology is used to illustrate the different approaches.     

Analysis of covariance structures

A general method is presented for estimating variance components when the experimental design has one random way of classification and a possibly unbalanced fixed classification. The procedure operates on a sample covariance matrix in which the fixed classes play the role of variables and the random classes correspond to observations. Cases are considered which assume (i) homogeneous and (ii) nonhomogeneous error variance, and (iii) arbitrary scale factors in the measurements and homogeneous error variance. The results include maximum-likelihood estimations of the variance components and scale factors, likelihood-ratio tests of the goodness-of-fit of the model assumed for the design, and large-sample variances and covariances of the estimates. Applications to mental test data are presented. In these applications the subjects constitute the random dimension of the design, and a classification of the mental tests according to objective features of format or content constitute the fixed dimensions.Preparation of this paper has been supported in part by NSF Grant GB-939 and U. S. P. H. Grant GM-1286-01. Computer time was donated by the Computation Center, University of Chicago.Now at the University of Chicago.Now at the University of Georgia.